Consistent surface and bulk magnetic properties of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>MnBi</mml:mi> <mml:mn>6</mml:mn> </mml:msub> <mml:msub> <mml:mi>Te</mml:mi> <mml:mn>10</mml:mn> </mml:msub> </mml:mrow> </mml:math> observed by x-ray absorption spectroscopy
Bibliographic record
Abstract
In order to understand how magnetic moments in a magnetic topological insulator (MTI) interact with the topological surface states (TSS) to open an exchange gap, it is crucial to experimentally distinguish the surface magnetic properties from those of the bulk. Here we achieve this for the layered van der Waals intrinsic MTI MnBi6Te10 by using x-ray absorption spectroscopy (XAS) in the surface-sensitive total electron yield (TEY) and bulk-sensitive fluorescence yield (FY) mode. The TEY data show substantial x-ray magnetic circular dichroism and x-ray magnetic linear dichroism, resulting from robust surface ferromagnetism with out-of-plane oriented Mn moments. We introduce an approach to decompose the XAS signal in a Fourier series, allowing us to extract the rather sharp resonant Mn edges, which overlap with a strong but only gradually fluctuating Te signal. We show that the experimental TEY and FY data, measured both with circular and linear light polarization, can all be fitted with a multiplet ligand field theory model with the same values for the model parameters. This reveals a close similarity between the surface and bulk electronic and magnetic properties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".